Clustering of self-motion selectivity and visual response properties in macaque area MSTd

Abstract

Neurons in the dorsal subdivision of the medial superior temporal area (MSTd) show directionally selective responses to both visual (optic flow) and vestibular stimuli that correspond to translational or rotational movements of the subject. Previous work has shown that MSTd neurons are clustered within the cortex according to their directional preferences for optic flow, suggesting that there may be a topographic mapping of self-motion vectors in MSTd. If MSTd provides a multisensory representation of self-motion information, then MSTd neurons may also be expected to show clustering according to their directional preferences for vestibular signals, but this has not been tested previously. We have examined clustering of vestibular signals by comparing the tuning of isolated single units (SUs) with the undifferentiated multiunit (MU) activity of several neighboring neurons recorded from the same microelectrode. We find that directional preferences for both translational and rotational vestibular stimuli, like those for optic flow, are clustered within area MSTd. MU activity often shows significant tuning for vestibular stimuli, although this MU selectivity is generally weaker for translation than for rotation. When directional tuning is observed in MU activity, the direction preference generally agrees closely with that of a simultaneously recorded SU. We also examined clustering of visual receptive field properties in MSTd by analyzing receptive field maps obtained using a reverse-correlation technique. We find that both the local directional preferences and overall spatial receptive field profiles are well clustered in MSTd. Overall, our findings have implications for how visual and vestibular signals regarding self-motion may be decoded from populations of MSTd neurons.

FIG. 1.

A: schematic illustration of the 26 rotational and translational directions tested. The 26 vectors sample all possible combinations of azimuth and elevation, in 45° increments, on a sphere. B, left: definition of azimuth angles. Right: definition of elevation angles. Straight arrows illustrate the direction of translation. Curved arrows illustrate the axis of rotation (according to the right-hand rule). C: reverse correlation stimulus for mapping medial superior temporal area (MSTd) receptive fields. The stimulus consisted of a 4 × 4 grid of stimulus subfields moving independently in one of 8 directions.

FIG. 2.

Example data from an MSTd neuron tested in the vestibular (top row) and visual (bottom row) translation conditions. A: 3-dimensional (3D) direction tuning profiles are shown for single-unit (SU, left column) and multiunit (MU, right column) activity. Color contour maps show the mean firing rate as a function of azimuth and elevation angles. Each contour map shows the Lambert cylindrical equal-area projection of the original spherical data. B: cross-correlation function between SU and MU responses. The abscissa is the time lag and the ordinate is the number of coincidences. The black curve represents the cross-correlation between SU and MU before SU spikes were excluded from MU. The red curve illustrates the cross-correlation after SU spikes were removed from the MU signal.

FIG. 3.

Example data from an MSTd neuron tested in the vestibular (top row) and visual (bottom row) rotation conditions. Format as described for Fig. 2.

FIG. 4.

Averaged cross-correlation function for all pairs of SU and MU tested using the translation (n = 287) or rotation (n = 81) protocols. Translation and rotation data have been pooled. The solid black line shows the raw average cross-correlation before SU spikes were excluded from the MU signal. The dashed black lines represent ±1 SD around this mean. The solid red line shows the average cross-correlation function after SU spikes were removed from the MU signal. Dashed red lines represent ±1 SD around this mean.

FIG. 5.

Quantitative summary of peak response (R_max − spont) and tuning strength (direction discrimination index [DDI]) derived from MU and SU responses. In each panel, data from SUs are plotted on the x-axis and data from the corresponding MU responses are plotted on the y-axis. Red and cyan symbols represent data from vestibular and visual conditions, respectively. A: comparison of SU and MU peak responses for the vestibular translation (n = 287) and visual translation (n = 272) conditions. B: comparison of SU and MU peak responses for the vestibular rotation (n = 81) and visual rotation (n = 66) conditions. C: comparison of SU and MU DDI values for the translation conditions. Closed (open) circles: neurons with (without) significant MU tuning (ANOVA, P < 0.05). D: comparison of SU and MU DDIs for the rotation conditions.

FIG. 6.

Summary of differences in direction tuning between SU and MU responses. In A and B, histograms show the distribution of the difference in 3D preferred directions, |Δ preferred direction|, between corresponding SU and MU responses (|Δ preferred direction| is computed as the smallest angle between the pair of preferred direction vectors in 3D). A: histograms of |Δ preferred direction| between SU and MU for the vestibular translation condition (n = 72/285, magenta) and the visual translation condition (n = 219/270, cyan). Note that data are shown here only for recordings in which both SU and MU responses showed significant tuning. B: histograms of |Δ preferred direction| for the vestibular rotation (n = 56/81) and visual rotation (n = 57/66) conditions. C and D show distributions of correlation coefficients (R_SU–MU) computed by comparing SU and MU tuning profiles. C: distributions of R_SU–MU are shown for the vestibular translation (n = 285) and visual translation (n = 270) conditions. Filled bars denote values of R_SU–MU that are significantly different from zero. D: distributions of R_SU–MU are shown for the vestibular rotation (n = 81) and visual rotation (n = 66) conditions.

FIG. 7.

Congruency of visual and vestibular tuning in SU and MU responses. A: congruency of SU responses for translation. The distribution of differences in 3D direction preference between visual and vestibular responses (|Δ preferred direction|) is bimodal, indicating roughly equal numbers of “congruent” and “opposite” cells. Data are shown for the subset of SUs with significant direction tuning in both visual and vestibular conditions. B: analogous data are shown for MU activity measured during the translation protocol. C: congruency (|Δ preferred direction|) for MU responses is plotted against that for SU responses. Data are shown for recording sites with significant SU and MU tuning for both visual and vestibular conditions. D: congruency of SU responses for the rotation protocol. E: congruency of MU responses to rotation stimuli. F: comparison of congruency between SU and MU responses obtained during the rotation protocol.

FIG. 8.

Summary tuning curves comparing SU and MU responses to translation and rotation stimuli. For each neuron, an azimuth tuning curve was obtained from the subset of directions lying in the horizontal plane. SU tuning curves (open symbols) show the average response of all SUs with significant tuning in the horizontal plane. The data are aligned to the peak response of each SU and spontaneous activity is subtracted before averaging. MU tuning curves (filled symbols) show the average MU responses (after subtracting spontaneous activity). MU data were aligned to the peak response of each corresponding SU. A: data from the vestibular translation condition. B: data from the visual translation condition. Note that MU tuning is stronger and more reliable compared with vestibular translation. C: average responses from the vestibular rotation condition. D: average responses from the visual rotation condition.

FIG. 9.

Direction–time receptive fields (RFs) are shown as contour plots for an example of SU (A) and MU (B) activity recorded simultaneously. In this case, the stimulated region of the visual field (90 × 90°) was divided into a 4 × 4 grid of 16 locations. Each subfield spanned 15 × 15 cm on the 60 × 60 cm tangent screen (viewed from 30 cm). As a result, the exact angular subtense of each subfield varied somewhat with its location. At each location, the stimulus could move in one of 8 directions. For each location, the neural response is cross-correlated with the motion impulse sequence (see methods). The direction of motion is indicated along the horizontal axis (with 0° indicating rightward and 90° indicating upward) and the reverse-correlation delay is indicated along the vertical axis. A “+” in the center denotes the center of the display screen where the monkey fixated. The optimal reverse-correlation delay is indicated by the black horizontal line in each panel.

FIG. 10.

Direction tuning curves at the peak response latency (T_peak = 82 ms) are shown for the same SU and MU data illustrated in Fig. 9. For each location in the stimulus grid, filled (open) circles show the MU (SU) response to 8 different directions of motion, 45° apart. The solid (dashed) curve is the best-fitting wrapped Gaussian function for MU (SU).

FIG. 11.

Summary of differences in direction tuning between SU and MU responses for each location tested within the receptive fields of a population of neurons. A: the scatterplot shows the relationship between the vector sum of normalized responses for SU and MU activity. Closed (open) circles: locations with (without) significant direction tuning for MU responses (P < 0.05). B: histogram of the differences between SU and MU direction preferences for all RF locations at which both signals showed significant tuning.

FIG. 12.

Example of spatial RF structure derived from reverse-correlation measurements. Two-dimensional (2D) spatial (X–Y) RFs are shown as contour plots for an example data set. Positive x values indicate the right visual hemifield and positive y values indicate the upper visual field. A: SU receptive field profile. Each point in the RF map represents the amplitude of the direction tuning curve obtained at the peak response latency. B: MU receptive field profile. C and D: 2D Gaussian fits to the spatial RF profiles of the SU and MU responses, respectively. The full width at half-maximum along the x dimension (FWHMx) is 38° for the SU and 41° for the MU; the full width at half-maximum along the y dimension (FWHMy) is 42° for the SU and 38° for the MU. The center of the RF is located at (−1.5°, −5.4°) for the SU response and (2.5°, −0.89°) for the MU response.

FIG. 13.

Summary of RF overlap between SU and MU responses. A: distribution of the normalized RF separation, which is defined as the distance between the centers of the SU and MU RFs normalized by the average width of the SU and MU RFs. Hatched and filled bars show normalized separations measured along the horizontal and vertical dimensions, respectively. B: comparison of receptive field sizes, FWHMx (open symbols) and FWHMy (filled symbols), between SU and MU responses.